{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T14:26:35Z","timestamp":1775658395054,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T00:00:00Z","timestamp":1705881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002848","name":"Chilean government through ANID\u2019s Fondecyt Regular Project","doi-asserted-by":"publisher","award":["1221091"],"award-info":[{"award-number":["1221091"]}],"id":[{"id":"10.13039\/501100002848","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study aims to develop and implement a methodology for retrieving bio-optical parameters in a lagoon located in the Biob\u00edo region, South-Central Chile, by analyzing time series of Landsat-8 OLI satellite images. The bio-optical parameters, i.e., chlorophyll-a (Chl-a, in mg\u00b7m\u22123) and turbidity (in NTU) were measured in situ during a satellite overpass to minimize the impact of atmospheric distortions. To calibrate the satellite images, various atmospheric correction methods (including ACOLITE, C2RCC, iCOR, and LaSRC) were evaluated during the image preprocessing phase. Spectral signatures obtained from the scenes for each atmospheric correction method were then compared with spectral signatures acquired in situ on the water surface. In short, the ACOLITE model emerged as the best fit for the calibration process, reaching R2 values of 0.88 and 0.79 for Chl-a and turbidity, respectively. This underlies the importance of using inversion models, when processing water surfaces, to mitigate errors due to aerosols and the sun-glint effect. Subsequently, reflectance data derived from the ACOLITE model were used to establish correlations between various spectral indices and the in situ data. The empirical retrieval models (based on band combinations) yielding superior performance, with higher R2 values, were subjected to a rigorous statistical validation and optimization by applying a bootstrapping approach. From this process the green chlorophyll index (GCI) was selected as the optimal choice for constructing the Chl-a retrieval model, reaching an R2 of 0.88, while the red + NIR spectral index achieved the highest R2 value (0.79) for turbidity analysis, although in the last case, it was necessary to incorporate data from several seasons for an adequate model training. Our analysis covered a broad spectrum of dates, seasons, and years, which allowed us to search deeper into the evolution of the trophic state associated with the lake. We identified a striking eight-year period (2014\u20132022) characterized by a decline in Chl-a concentration in the lake, possibly attributable to governmental measures in the region for the protection and conservation of the lake. Additionally, the OLI imagery showed a spatial pattern varying from higher Chl-a values in the northern zone compared to the southern zone, probably due to the heat island effect of the northern urban areas. The results of this study suggest a positive effect of recent local regulations and serve as the basis for the creation of a modern monitoring system that enhances traditional point-based methods, offering a holistic view of the ongoing processes within the lake.<\/jats:p>","DOI":"10.3390\/rs16020427","type":"journal-article","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T06:49:31Z","timestamp":1705906171000},"page":"427","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7879-7094","authenticated-orcid":false,"given":"Santiago","family":"Y\u00e9pez","sequence":"first","affiliation":[{"name":"Departamento Manejo de Bosques y Medio Ambiente, Facultad de Ciencias Forestales, Universidad de Concepci\u00f3n, Concepci\u00f3n 4070386, Chile"}]},{"given":"Germ\u00e1n","family":"Vel\u00e1squez","sequence":"additional","affiliation":[{"name":"Instituto de Geolog\u00eda Econ\u00f3mica Aplicada, Universidad de Concepci\u00f3n, Concepci\u00f3n 4070386, Chile"},{"name":"UMR 5563 G\u00e9osciences Environnement Toulouse, Universit\u00e9 de Toulouse, CNRS-IRD-OMP-CNES, 31000 Toulouse, France"}]},{"given":"Daniel","family":"Torres","sequence":"additional","affiliation":[{"name":"Departamento Manejo de Bosques y Medio Ambiente, Facultad de Ciencias Forestales, Universidad de Concepci\u00f3n, Concepci\u00f3n 4070386, Chile"},{"name":"Programa de M\u00e1ster en Ingenier\u00eda de Montes, E.T.S.I Escuela T\u00e9cnica Superior de Ingenier\u00eda, Universidad de Huelva, 21071 Huelva, Spain"}]},{"given":"Rodrigo","family":"Saavedra-Passache","sequence":"additional","affiliation":[{"name":"Doctoral Program in Advanced Forestry Engineering, E.T.S.I Montes, Forestal y Medio Natural, Universidad Politecnica de Madrid\u2014UPM, 28040 Madrid, Spain"}]},{"given":"Martin","family":"Pincheira","sequence":"additional","affiliation":[{"name":"Forestal ARAUCO S.A., Gerencia de Planificaci\u00f3n y Mejora Continua, Concepci\u00f3n 4030000, Chile"}]},{"given":"Hayleen","family":"Cid","sequence":"additional","affiliation":[{"name":"Departamento de Geof\u00edsica, Facultad de Ciencias F\u00edsicas y Matem\u00e1ticas, Universidad de Concepci\u00f3n, Concepci\u00f3n 4070386, Chile"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0550-0253","authenticated-orcid":false,"given":"Lien","family":"Rodr\u00edguez-L\u00f3pez","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Arquitectura y Dise\u00f1o, Universidad San Sebasti\u00e1n, Lientur 1457, Concepci\u00f3n 4030000, Chile"}]},{"given":"Angela","family":"Contreras","sequence":"additional","affiliation":[{"name":"Departamento Ciencias de la Tierra, Ciencias Qu\u00edmicas, Universidad de Concepci\u00f3n, Concepci\u00f3n 4030000, Chile"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4661-8274","authenticated-orcid":false,"given":"Fr\u00e9d\u00e9ric","family":"Frappart","sequence":"additional","affiliation":[{"name":"ISPA, INRAE, Bordeaux Sciences Agro, 33140 Villenave d\u2019Ornon, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6244-4289","authenticated-orcid":false,"given":"Jordi","family":"Crist\u00f3bal","sequence":"additional","affiliation":[{"name":"Efficient Use of Water in Agriculture Program, Institute of Agrifood Research and Technology, Fruitcentre, Parc Cient\u00edfic i Tecnol\u00f2gic Agroalimentari de Lleida 23, 25003 Lleida, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6924-1641","authenticated-orcid":false,"given":"Xavier","family":"Pons","sequence":"additional","affiliation":[{"name":"Grumets Research Group, Departament de Geografia, Edifici B. Universitat Aut\u00f2noma de Barcelona, 08193 Bellaterra, Catalonia, Spain"}]},{"given":"Neftali","family":"Flores","sequence":"additional","affiliation":[{"name":"Departamento Manejo de Bosques y Medio Ambiente, Facultad de Ciencias Forestales, Universidad de Concepci\u00f3n, Concepci\u00f3n 4070386, Chile"}]},{"given":"Luc","family":"Bourrel","sequence":"additional","affiliation":[{"name":"UMR 5563 G\u00e9osciences Environnement Toulouse, Universit\u00e9 de Toulouse, CNRS-IRD-OMP-CNES, 31000 Toulouse, France"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,22]]},"reference":[{"key":"ref_1","unstructured":"Millennium Ecosystem Assessment (2005). Ecosystems and Human Well-Being, Island Press."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Cooke, G.D., Welch, E.B., Peterson, S., and Nichols, S.A. (2016). 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